Staging preclinical Alzheimer disease with CSF biomarkers Career development plan I have been interested in Alzheimer's disease (AD) since high school. I did research on AD in college, completed a PhD in Neurosciences focused on AD, underwent medical training and a neurology residency, and became a dementia specialist. I currently see patients with memory problems in the clinic, perform clinical assessments for AD research and assist with two drug trials for prevention of AD. Although my research background was in a wet lab doing basic neuroscience, at the end of 2015 I decided to make a major career change to align my clinical training and research interests. I have been learning new skills, including statistical analysis, so that I can perform meaningful clinical research. I still have much to learn and would benefit tremendously from a four year mentored career development award. There is a major need in the AD field for a test that reliably predicts if and when cognitively normal individuals will develop AD dementia. I believe that I am uniquely positioned to investigate this topic. I am a junior faculty member at Washington University's Knight Alzheimer's Disease Research Center (ADRC), which has one of the largest and best characterized repositories of AD cerebrospinal fluid (CSF) and plasma in the world. My mentors include Dr. John Morris, a world expert on longitudinal clinical research studies of AD, and Dr. Anne Fagan, a leader in CSF biomarkers of AD. I have assembled a group of collaborators, at Washington University and at other institutions, with expertise in clinical chemistry, statistics, brain imaging, and cognitive testing. All these individuals will serve to advise and guide me as I develop my skills and experience. I have formulated a training plan that will increase my knowledge of fluid biomarkers, statistics and statistical computing, imaging, and psychometrics. Training activities include formal coursework, conferences, meetings and seminars. The research plan I have detailed will provide opportunities to measure emerging biomarkers in CSF samples, perform complex statistical analyses of biomarker levels, learn about the generation of various types of brain imaging measures and evaluate performance on multiple cognitive tests. At the conclusion of the four year career development award, I expect to be a skilled, multidisciplinary investigator with independent funding and an independent research program. Research plan We propose to develop and validate a staging system for preclinical Alzheimer disease (AD) using a panel of seven cerebrospinal fluid (CSF) biomarkers. Improved staging of preclinical AD would be helpful to clinicians and patients who desire to know their risk for development of AD dementia within the next 20, 10, 5 or 2 years. Further, more precise staging of preclinical AD in clinical drug trials would allow refinement of enrollment criteria and determination of when treatments are most effective at slowing progression of the disease. It is unlikely that a single brain imaging modality or fluid biomarker could reflect the complex pathophysiology of AD. However, a single sample of cerebrospinal fluid (CSF) offers an opportunity to measure many of the processes occurring along the AD pathologic cascade, from amyloid deposition to tau aggregation/release to injury/destruction of synapses to inflammation to neuronal cell death. The potentially rich information offered by CSF, including on processes not well reflected by current imaging techniques, may allow better staging of preclinical AD and improve our ability to predict when individuals will develop dementia. We will formulate a biomarker defined preclinical AD staging system using levels of CSF A?42, tau, ptau, the pre-synaptic protein synaptosomal-associated protein-25 (SNAP-25), the post-synaptic calmodulin binding protein neurogranin, the neuronal calcium sensor visinin-like protein 1 (VILIP-1) and the inflammatory marker YKL-40. With CSF biomarker data from a cohort of families carrying Autosomal Dominant Alzheimer Disease (ADAD) mutations, we will plot a time course of biomarker changes in ADAD mutation carriers versus non-carriers. We will use the biomarker data to create a CSF biomarker defined staging system for preclinical AD. We will examine whether this staging system accurately estimates the time until dementia onset using longitudinal data. We will then translate and optimize this staging system, created in an ADAD cohort, to a cohort at risk for late onset AD (LOAD) from Washington University. Next we will validate the LOAD staging system in an independent cohort at risk for LOAD from Johns Hopkins University. Finally, we will evaluate how well the staging system correlates with imaging biomarkers of AD, including hippocampal volume, amyloid PET, and tau PET.